Portrait of Cleber Jorge Amaral

Background

Artisan November 2025 – present · remote

Full-stack engineer building the backend of a production AI-powered BDR agent: LLM orchestration, asynchronous task workers, and frontend integration. The system serves about 1,000 users and processes roughly 25,000 leads per day. I also work on cloud infrastructure on GCP and DigitalOcean, including containerization, CI/CD, and automated deployments.

IFSC April 2016 – present · sabbatical

Lecturer in the Telecommunications area at the Federal Institute of Santa Catarina (Campus São José), teaching programming, computer architecture, networks, and related topics. I have also led two electric-vehicle (EV) charging infrastructure projects to production — GCP infrastructure, Python and Laravel backends, plus web, Android, and iOS applications.

Electronics industry ~15 years · before 2016

Worked as an entrepreneur and later at Automatiza and Intelbras on hardware and software product development and R&D team management, building the systems-programming foundation for later full-stack, cloud, and AI work.

PhD in Automation and Systems UFSC · 2022

Dissertation: GoOrg: A model to automatically design organisations for Multi-Agent Systems. Graduate Program in Automation and Systems Engineering (PPGEAS).

Earlier degrees: Master’s in Mechatronics (IFSC, 2016), MBA in Business Management (Univali, 2012), undergraduate degree in Electronic Systems (CEFET-SC, 2007), and technical studies in Electronics and Microprocessor Systems (ETFSC, 1999).

Technical focus

  • Backend & APIs Python (FastAPI / Flask), TypeScript, Laravel, REST APIs, Java, async workers, microservices
  • AI / LLM LLM orchestration, agent workflows, prompt engineering, production AI systems
  • Frontend TypeScript, JavaScript, React integration, web applications
  • Databases PostgreSQL, MySQL, Microsoft SQL Server
  • Cloud & DevOps GCP, AWS, DigitalOcean, containers, CI/CD, deployment automation
  • Other System design, Multi-Agent Systems, teaching and mentoring

Interests

Organisations and development tools for Multi-Agent Systems (MAS), Distributed Systems, Machine Learning, and Programming Languages — with particular interest in how classical MAS ideas meet modern LLM agent orchestration.

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